• Journal of KIISE:Databases
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• v.33 no.1
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• pp.56-68
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• 2006

For tracing tag locations, the trajectories should be modeled and indexed in radio frequency identification (RFID) systems. The trajectory of a tag can be represented as a line that connects two spatiotemporal locations captured when the tag enters and leaves the vicinity of a reader. If a tag enters but does not leave a reader, its trajectory is represented only as a point captured at entry. Because the information that a tag stays in a reader is missing from the trajectory represented only as a point, it is impossible to find the tag that remains in a reader. To solve this problem we propose the data model in which trajectories are defined as time-parameterized intervals and new index scheme called the Time Parameterized Interval R-tree. We also propose new insert and split algorithms that reduce the area of nodes to enable efficient query processing. We evaluate the performance of the proposed index scheme and compare it with previous indexes on various datasets.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.495-508
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• 2005

Moving objects are spatiotemporal data that change their location or shape continuously over time. Their location coordinates are periodically measured and stored i3l the application systems. The linear function is mainly used to estimate the location information that is not in the system at the query time point. However, a new method is needed to improve uncertainties of the location representation, because the location estimation by linear function induces the estimation error. This paper proposes an application method of the cubic spline interpolation in order to reduce deviation of the location estimation by linear function. First, we define location information of the moving object on the two-dimensional space. Next, we apply the cubic spline interpolation to location estimation of the proposed data model and describe algorithm of the estimation operation. Finally, the precision of this estimation operation model is experimented. The experimentation comes out more accurate results than the method by linear function.

• Journal of Radiation Industry
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• v.8 no.2
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• pp.123-132
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• 2014

After the nuclear accident of the Fukushima Dai-ichi Nuclear Power Plants (FDNPPs) on 11 March 2011, a large amount of radioactive materials has been released into the atmosphere and the ocean. A compartment model is used to evaluate the circulation characteristics and the spatiotemporal concentration distributions of radionuclides in the ocean. In the comparison with observed concentrations of $^{137}Cs$ in seawater, calculated concentrations by the compartment model were well agreed with them. On the basis of these results, we performed evaluation of the effective dose and the cancer risk. In the early stage of the accident, the effective doses from ingestion of the seafood near the Fukushima region were much higher than 1 mSv which is the value of the annual effective dose limit to individual recommended by the International Commission on Radiological Protection (ICRP). However, the effective doses by ingestion of the seafood decreased below 1 mSv as distance from the FDNPPs increased and time passed. In addition, it was estimated that the cancer risks by intake of the contaminated marine products were less than natural occurrence probability of cancer. Consequently, it was inferred that the health risk due to the $^{137}Cs$ was low after since mid-term period of the accident.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.103-115
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• 2018

The uncertainty of climate scenarios, as initial information, is one of the significant factors among uncertainties of climate change impacts and vulnerability assessments. In this sense, the quantification of the uncertainty of climate scenarios is essential to understanding these assessments of impacts and vulnerability for adaptation to climate change. Here we quantified the precision of surface temperature of ensemble scenarios (high resolution (1km) RCP4.5 and 8.5) provided by Korea Meteorological Administration, with spatiotemporal variation of the standard deviation of them. From 2021 to 2050, the annual increase rate of RCP8.5 was higher than that of RCP4.5 while the annual variation of RCP8.5 was lower than that of RCP4.5. The standard deviations of ensemble scenarios are higher in summer and winter, particularly in July and January, when the extreme weather events could occur. In general, the uncertainty of ensemble scenarios in summer were lower than those in winter. In spatial distribution, the standard deviation of ensemble scenarios in Seoul Metropolitan Area is relatively higher than other provinces, while that of Yeongnam area is lower than other provinces. In winter, the standard deviations of ensemble scenarios of RCP4.5 and 8.5 in January are higher than those of December. Especially, the standard deviation of ensemble scenarios is higher in the central regions including Gyeonggi, and Gangwon, where the mean surface temperature is lower than southern regions along with Chungbuk. Such differences in precisions of climate ensemble scenarios imply that those uncertainty information should be taken into account for the implementation of national climate change policy.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.260-260
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• 2017

This study aims to compare the performance of TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-stability model) and TiVaSS (Time-variant Slope Stability model) in the prediction of rainfall-induced shallow landslides. TRIGRS employs one-dimensional (1-D) subsurface flow to simulate the infiltration rate, whereas a three-dimensional (3-D) model is utilized in TiVaSS. The former has been widely used in landslide modeling, while the latter was developed only recently. Both programs are used for the spatiotemporal prediction of shallow landslides caused by rainfall. The present study uses the July 2011 landslide event that occurred in Mt. Umyeon, Seoul, Korea, for validation. The performance of the two programs is evaluated by comparison with data of the actual landslides in both location and timing by using a landslide ratio for each factor of safety class ( index), which was developed for addressing point-like landslide locations. In addition, the influence of surface flow on landslide initiation is assessed. The results show that the shallow landslides predicted by the two models have characteristics that are highly consistent with those of the observed sliding sites, although the performance of TiVaSS is slightly better. Overland flow affects the buildup of the pressure head and reduces the slope stability, although this influence was not significant in this case. A slight increase in the predicted unstable area from 19.30% to 19.93% was recorded when the overland flow was considered. It is concluded that both models are suitable for application in the study area. However, although it is a well-established model requiring less input data and shorter run times, TRIGRS produces less accurate results.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.165-175
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• 2021

Groundwater is used in many areas in food industry such as food manufacturing, food processing, cooking, and liquor industry etc. in Korea. As groundwater occupies a large portion of food industry, it is necessary to predict deterioration of water quality to ensure the safety of food water since using undrinkable groundwater has a ripple effect that can cause great harm or anxiety to food users. In this study, spatiotemporal data aggregation method was used in order to obtain spatially representative data, which enable prediction of groundwater quality change in a small watershed. In addition, a highly reliable predictive model was developed to estimate long-term changes in groundwater quality by applying a non-parametric segmented regression technique. Two pilot watersheds were selected where a large number of companies use groundwater for food water, and the appropriateness of the model was assessed by comparing the model-produced values with those obtained by actual measurements. The result of this study can contribute to establishing a customized food water management system utilizing big data that respond quickly, accurately, and preemptively to changes in groundwater quality and pollution. It is also expected to contribute to the improvement of food safety management.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.61-75
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• 2021

This study aims to assess the changes in crop water requirement of paddy and upland according to future climate and land use changes scenarios. Changes in the spatiotemporal distribution of temperature and precipitation are factors that lower the stability of agricultural water supply, and predicting the changes in crop water requirement in consideration of climate change can prevent the waste of limited water resources. Meanwhile, due to the recent changes in the agricultural product consumption structure, the area of paddy and upland has been changing, and it is necessary to consider future land use changes in establishing an appropriate water use plan. Climate change scenarios were derived from the four GCMs of the CMIP6, and climate data were extracted under two future scenarios, namely SSP1-2.6 and SSP5-8.5. Future land use changes were predicted using the FLUS (Future Land Use Simulation) model. Crop water requirement in paddy was calculated as the sum of evapotranspiration and infiltration based on the water balance in a paddy field, and crop water requirement in upland was estimated as the evapotranspiration value by applying Penman-Monteith method. It was found that the crop water requirement for both paddy and upland increased as we go to the far future, and the degree of increase and variability by time showed different results for each GCM. The results derived from this study can be used as basic data to develop sustainable water resource management techniques considering future watershed environmental changes.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.5
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• pp.1-11
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• 2021

Soil moisture plays a critical role in hydrological processes, land-atmosphere interactions and climate variability. It can limit vegetation growth as well as infiltration of rainfall and therefore very important for agriculture sector and food protection. Recently, due to the increased damage from drought caused by climate change, there is a frequent occurrence of shortage of agricultural water, making it difficult to supply and manage stable agricultural water. Efficient water management is necessary to reduce drought damage, and soil moisture management is important in case of upland crops. In this study, soil moisture was calculated based on the water balance model, and the suitability of soil moisture data was verified through the application. The regional soil moisture was calculated based on the meteorological data collected by the meteorological station, and applied the Runs theory. We analyzed the spatiotemporal variability of soil moisture and drought impacts, and analyzed the correlation between actual drought impacts and drought damage through correlation analysis of Standardized Precipitation Index (SPI). The soil moisture steadily decreased and increased until the rainy season, while the drought size steadily increased and decreased until the rainy season. The regional magnitude of the drought was large in Gyeonggi-do and Gyeongsang-do, and in winter, severe drought occurred in areas of Gangwon-do. As a result of comparative analysis with actual drought events, it was confirmed that there is a high correlation with SPI by each time scale drought events with a correlation coefficient.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.767-785
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• 2021

With the rapid development of information technology, it is now possible to analyze the spatial patterns of cultivated land and its evolution by combining GIS, geostatistical analysis models and spatiotemporal big data for the dynamic monitoring and management of cultivated land resources. The spatial pattern of cultivated land and its evolutionary patterns in Luoyang City, China from 2009 to 2019 were analyzed using spatial autocorrelation and spatial autoregressive models on the basis of GIS technology. It was found that: (1) the area of cultivated land in Luoyang decreased then increased between 2009 and 2019, with an overall increase of 0.43% in 2019 compared to 2009, with cultivated land being dominant in the overall landscape of Luoyang; (2) cultivated land holdings in Luoyang are highly spatially autocorrelated, with the 'high-high'-type area being concentrated in the border area directly north and northeast of Luoyang, while the 'low-low'-type area is concentrated in the south and in the municipal area of Luoyang, and being heavily influenced by topography and urbanization. The expansion determined during the study period mainly took place in the Luoyang City, with most of it being transferred from the 'high-low'-type area; (3) elevation, slope and industrial output values from analysis of the bivariate spatial autocorrelation and spatial autoregressive models of the drivers all had significant effects on the amount of cultivated land holdings, with elevation having a positive effect, and slope and industrial output having a negative effect.

• Journal of Environmental Health Sciences
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• v.47 no.2
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• pp.144-154
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• 2021

Objectives: This study was intended to identify hazard contribution by region, media, and chemical by calculating a hazard-based index using pollutant release and transfer register (PRTR) data. Methods: PRTR data for the period 2011 to 2016 was analyzed to examine the regional trends in toxic releases in terms of quantity and to create a corresponding hazard-based index. For the hazard-based index, the Risk-Screening Environmental Indicators (RSEI) Model was used. Results: The results of the trend analysis show that total releases decreased slightly, but health hazard levels increased consistently. According to the outcome of regional contribution analysis of the hazard-based index, Chungcheongnam-do, Jeollabuk-do and Gyeonggi-do Provinces showed a high ratio in the index for air and water release pollutants, while Gyeongsangbuk-do and Gyeongsangnam-do Provinces showed a high ratio in the index of soil release and waste transfer pollutants. Also, as a result of the analysis of the top ranked substances in the hazard-based index, it was found that chromium, cobalt and its compounds, and ethylene oxide contributed greatly to air release substances, while chromium, benzene, and lead and its compounds contributed greatly to water release substances. Conclusion: These results showed considerable disparities between total release and health hazard levels, especially in the analysis of contribution by regions and by chemical substance. Therefore, the hazard-based index should be used both to support a more comprehensive and robust approach to screening of chemicals for environmental health policy and for management.